scipy.spatial.distance.yule#

scipy.spatial.distance.yule(u, v, w=None)[source]#

Compute the Yule dissimilarity between two boolean 1-D arrays.

The Yule dissimilarity is defined as

\[\frac{R}{c_{TT} * c_{FF} + \frac{R}{2}}\]

where \(c_{ij}\) is the number of occurrences of \(\mathtt{u[k]} = i\) and \(\mathtt{v[k]} = j\) for \(k < n\) and \(R = 2.0 * c_{TF} * c_{FT}\).

Parameters:

u(N,) array_like, bool: Input array.
v(N,) array_like, bool: Input array.
w(N,) array_like, optional: The weights for each value in u and v. Default is None, which gives each value a weight of 1.0

Returns:

Examples

>>> from scipy.spatial import distance
>>> distance.yule([1, 0, 0], [0, 1, 0])
2.0
>>> distance.yule([1, 1, 0], [0, 1, 0])
0.0